First study on the determination of baseline biomarkers in Mimachlamys varia for an intra-port environmental biomonitoring in French Atlantic coastline (La Rochelle). (September 2022)

• Record Type: Journal Article
• Authors: Barbarin, Marine; Muttin, Frédéric; Thomas, Hélène
• Is Part Of: Marine pollution bulletin. Volume 182(2022)
• Publication Date: 2022-09
• Subjects: Bivalve -- Biomarkers -- Environmental quality -- Baseline -- Biomonitoring; Marine pollution -- Periodicals; Marine Biology -- Periodicals; Water Pollution -- Periodicals; Mer -- Pollution -- Périodiques; Publications périodiques; Pollution des mers; Lutte antipollution; Electronic journals; 363.7394
• DOI: 10.1016/j.marpolbul.2022.113979
• Languages: English
• ISSNs: 0025-326X

Abstract

Abstract: The characterization of organic and inorganic environmental pollution in coastal ecosystems, such as port areas, is complex and difficult to carry out due to the effect of environmental variables, as well as anthropic activities. For this study, the objective was to define a statistical method, taking into account the confounding factors influence, to define reference values for biomarkers in the black scallop ( Mimachlamys varia ). Thus, for five biomarkers (SOD (Superoxyde Dismutase), GST (Glutathion-S Transferase), MDA (Malondialdehyde), AChE (Acetylcholinesterase) and LAC (Laccase)), reference data could be described for individuals placed on sites more or less strongly impacted by specific environmental contaminations in port areas for more than two years, which had never been done before. All these results enabled us to calibrate and validate our approach in terms of active biomonitoring for the evaluation of a good ecological status of the environment of a port located on the French Atlantic coast. Highlights: Use of black scallops to assess the quality of the environment in the port area. Integration of confounding factors in the model to avoid environmental variations. Use of five biomarkers to assess the health status of individuals. Use of multilinear regression for statistical analysis. Proposed method to assess scallop health spatially and temporally.